def get_angles(self):
self.get_times()
tle1, tle2 = self.get_tle_lines()
orb = Orbital(self.spacecrafts_orbital[self.spacecraft_id],
line1=tle1,
line2=tle2)
sat_azi, sat_elev = orb.get_observer_look(self.times[:, np.newaxis],
self.lons, self.lats, 0)
sat_zenith = 90 - sat_elev
sun_zenith = astronomy.sun_zenith_angle(self.times[:, np.newaxis],
self.lons, self.lats)
alt, sun_azi = astronomy.get_alt_az(self.times[:, np.newaxis],
self.lons, self.lats)
del alt
sun_azi = np.rad2deg(sun_azi)
sun_azi = np.where(sun_azi < 0, sun_azi + 180, sun_azi - 180)
rel_azi = abs(sat_azi - sun_azi)
rel_azi = np.where(rel_azi > 180.0, 360.0 - rel_azi, rel_azi)
return sat_azi, sat_zenith, sun_azi, sun_zenith, rel_azi
def __call__(self, projectables, optional_datasets=None, **info):
"""Get the corrected reflectance when removing Rayleigh scattering. Uses
pyspectral.
"""
from pyspectral.rayleigh import Rayleigh
(vis, red) = projectables
if vis.shape != red.shape:
raise IncompatibleAreas
try:
(sata, satz, suna, sunz) = optional_datasets
except ValueError:
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
lons, lats = vis.info['area'].get_lonlats()
sunalt, suna = get_alt_az(vis.info['start_time'], lons, lats)
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(vis.info['start_time'], lons, lats)
sata, satel = get_observer_look(vis.info['satellite_longitude'],
vis.info['satellite_latitude'],
vis.info['satellite_altitude'],
vis.info['start_time'], lons, lats,
0)
satz = 90 - satel
del satel
LOG.info('Removing Rayleigh scattering and aerosol absorption')
# First make sure the two azimuth angles are in the range 0-360:
sata = np.mod(sata, 360.)
suna = np.mod(suna, 360.)
ssadiff = np.abs(suna - sata)
ssadiff = np.where(ssadiff > 180, 360 - ssadiff, ssadiff)
del sata, suna
atmosphere = self.info.get('atmosphere', 'us-standard')
aerosol_type = self.info.get('aerosol_type', 'marine_clean_aerosol')
corrector = Rayleigh(vis.info['platform_name'],
vis.info['sensor'],
atmosphere=atmosphere,
aerosol_type=aerosol_type)
try:
refl_cor_band = corrector.get_reflectance(sunz, satz, ssadiff,
vis.id.name, red)
except KeyError:
LOG.warning(
"Could not get the reflectance correction using band name: %s",
vis.id.name)
LOG.warning(
"Will try use the wavelength, however, this may be ambiguous!")
refl_cor_band = corrector.get_reflectance(sunz, satz, ssadiff,
vis.id.wavelength[1],
red)
proj = Dataset(vis - refl_cor_band, copy=False, **vis.info)
self.apply_modifier_info(vis, proj)
return proj
def parse_jaxa_hotspot_txt(self, file_path):
"""
Parse the JAXA Himawari-8/9 AHI hotspot text file and insert attrs into the Pandas DataFrame
Args:
file_path (str): File path to the JAXA Himawari-8/9 hotspot .csv
Returns:
hs_df (obj): DataFrame obj that contains attr of Himawari-8/9 hospot
"""
hs_ahi_df = pd.DataFrame()
cols_to_use_list = [0, 2, *(i for i in range(7, 24))]
date_col_list = [0]
names_list = ['date', 'satellite', 'lon', 'lat', 'viewzenang', 'viewazang', 'pixwid', 'pixlen', 't07',
't14', 't07_t14', 'meant07', 'meant14', 'meandt', 'sdt07', 'sdt14', 'sddt',
'ref3', 'ref4']
for file in glob.glob(file_path):
try:
log.debug(f'Reading {file}')
temp_hs_ahi_df = pd.read_csv(file, sep=",", skiprows=[0], \
header=None, usecols=cols_to_use_list, \
names=names_list, \
parse_dates=date_col_list)
temp_hs_ahi_df['satellite'] = 'Himawari-8/9'
except Exception as e:
log.error(f'Error reading {file}')
log.error(e)
continue
if len(temp_hs_ahi_df) > 0:
try:
temp_hs_ahi_df['solarazang'] = temp_hs_ahi_df.apply( \
lambda x: np.degrees(astronomy.get_alt_az(x['date'], x['lon'], x['lat'])[1]), axis=1)
temp_hs_ahi_df['solarzenang'] = temp_hs_ahi_df.apply( \
lambda x: astronomy.sun_zenith_angle(x['date'], x['lon'], x['lat']), axis=1)
temp_hs_ahi_df['relazang'] = temp_hs_ahi_df['solarazang'] - temp_hs_ahi_df['viewazang']
temp_hs_ahi_df['sunglint_angle'] = temp_hs_ahi_df.apply(compute_sun_glint_angle, axis=1)
except Exception as e:
temp_hs_ahi_df['sunglint_angle'] = np.nan
try:
temp_hs_ahi_df.loc[(temp_hs_ahi_df['date'].dt.hour >= 0) \
& (temp_hs_ahi_df['date'].dt.hour <= 11), 'daynight'] = 'day'
temp_hs_ahi_df.loc[temp_hs_ahi_df['date'].dt.hour > 11, \
'daynight'] = 'night'
temp_hs_ahi_df['date'] = temp_hs_ahi_df['date'].dt.strftime( \
"%d/%m/%Y %H:%M:%S")
except Exception as e:
date_from_file = datetime.strptime(filename[4:17], "%Y%m%d_%H%M")
temp_hs_ahi_df['date'] = date_from_file.strftime("%d/%m/%Y %H:%M:%S")
hs_ahi_df = pd.concat([hs_ahi_df, temp_hs_ahi_df])
if len(hs_ahi_df) > 0:
hs_ahi_df = hs_ahi_df.reset_index(drop=True)
self.hs_df = pd.concat([hs_ahi_df, self.hs_df])
def get_angles(self, vis):
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
lons, lats = vis.attrs['area'].get_lonlats_dask(chunks=vis.data.chunks)
suna = get_alt_az(vis.attrs['start_time'], lons, lats)[1]
suna = xu.rad2deg(suna)
sunz = sun_zenith_angle(vis.attrs['start_time'], lons, lats)
sata, satel = get_observer_look(vis.attrs['satellite_longitude'],
vis.attrs['satellite_latitude'],
vis.attrs['satellite_altitude'],
vis.attrs['start_time'], lons, lats, 0)
satz = 90 - satel
return sata, satz, suna, sunz
def get_angles(self):
"""Get azimuth and zenith angles.
Azimuth angle definition is the same as in pyorbital, but with
different units (degrees not radians for sun azimuth angles)
and different ranges.
Returns:
sat_azi: satellite azimuth angle
degree clockwise from north in range ]-180, 180],
sat_zentih: satellite zenith angles in degrees in range [0,90],
sun_azi: sun azimuth angle
degree clockwise from north in range ]-180, 180],
sun_zentih: sun zenith angles in degrees in range [0,90],
rel_azi: absolute azimuth angle difference in degrees between sun
and sensor in range [0, 180]
"""
self.get_times()
self.get_lonlat()
tle1, tle2 = self.get_tle_lines()
times = self.times
orb = Orbital(self.spacecrafts_orbital[self.spacecraft_id],
line1=tle1,
line2=tle2)
sat_azi, sat_elev = orb.get_observer_look(times[:, np.newaxis],
self.lons, self.lats, 0)
sat_zenith = 90 - sat_elev
sun_zenith = astronomy.sun_zenith_angle(times[:, np.newaxis],
self.lons, self.lats)
alt, sun_azi = astronomy.get_alt_az(times[:, np.newaxis], self.lons,
self.lats)
del alt
sun_azi = np.rad2deg(sun_azi)
rel_azi = get_absolute_azimuth_angle_diff(sun_azi, sat_azi)
# Scale angles range to half open interval ]-180, 180]
sat_azi = centered_modulus(sat_azi, 360.0)
sun_azi = centered_modulus(sun_azi, 360.0)
# Mask corrupt scanlines
for arr in (sat_azi, sat_zenith, sun_azi, sun_zenith, rel_azi):
arr[self.mask] = np.nan
return sat_azi, sat_zenith, sun_azi, sun_zenith, rel_azi
def __call__(self, projectables, optional_datasets=None, **info):
"""Get the corrected reflectance when removing Rayleigh scattering. Uses
pyspectral.
"""
from pyspectral.rayleigh import Rayleigh
(vis, blue) = projectables
if vis.shape != blue.shape:
raise IncompatibleAreas
try:
(sata, satz, suna, sunz) = optional_datasets
except ValueError:
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
sunalt, suna = get_alt_az(
vis.info['start_time'], *vis.info['area'].get_lonlats())
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(
vis.info['start_time'], *vis.info['area'].get_lonlats())
lons, lats = vis.info['area'].get_lonlats()
sata, satel = get_observer_look(vis.info['satellite_longitude'],
vis.info['satellite_latitude'],
vis.info['satellite_altitude'],
vis.info['start_time'],
lons, lats, 0)
satz = 90 - satel
del satel
LOG.info('Removing Rayleigh scattering and aerosol absorption')
ssadiff = np.abs(suna - sata)
ssadiff = np.where(ssadiff > 180, 360 - ssadiff, ssadiff)
del sata, suna
atmosphere = self.info.get('atmosphere', 'us-standard')
aerosol_type = self.info.get('aerosol_type', 'marine_clean_aerosol')
corrector = Rayleigh(vis.info['platform_name'], vis.info['sensor'],
atmosphere=atmosphere,
aerosol_type=aerosol_type)
refl_cor_band = corrector.get_reflectance(
sunz, satz, ssadiff, vis.id.wavelength[1], blue)
proj = Dataset(vis - refl_cor_band,
copy=False,
**vis.info)
self.apply_modifier_info(vis, proj)
return proj
def getSentinel2Geometry(startDateUTC, lengthDays, lat, lon, alt=0.0, mission="Sentinel-2a",
tleFile="../TLE/norad_resource_tle.txt"):
"""Calculate approximate geometry for Sentinel overpasses.
Approximate because it assumes maximum satellite elevation
is the time at which target is imaged.
:param startDateUTC: a datetime object specifying when to start prediction.
:type startDateUTC: object
:param lengthDays: number of days over which to perform calculations.
:type lengthDays: int
:param lat: latitude of target.
:type lat: float
:param lon: longitude of target.
:type lon: float
:param alt: altitude of target (in km).
:type alt: float
:param mission: mission name as in TLE file.
:type mission: str
:param tleFile: TLE file.
:type tleFile: str
:return: a python list containing instances of the sensorGeometry class arranged in date order.
:rtype: list
"""
orb = Orbital(mission, tleFile)
passes = orb.get_next_passes(startDateUTC, 24 * lengthDays, lon, lat, alt)
geomList = []
for p in passes:
look = orb.get_observer_look(p[2], lon, lat, alt)
vza = 90 - look[1]
vaa = look[0]
sza = ast.sun_zenith_angle(p[2], lon, lat)
saa = np.rad2deg(ast.get_alt_az(p[2], lon, lat)[1])
if sza < 90 and vza < 10.3:
thisGeom = sensorGeometry()
thisGeom.date_utc = p[2]
thisGeom.vza = vza
thisGeom.vaa = vaa
thisGeom.sza = sza
thisGeom.saa = saa
geomList.append(thisGeom)
return geomList
def get_angles(self, vis):
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
lons, lats = vis.attrs['area'].get_lonlats_dask(
chunks=vis.data.chunks)
sunalt, suna = get_alt_az(vis.attrs['start_time'], lons, lats)
suna = xu.rad2deg(suna)
sunz = sun_zenith_angle(vis.attrs['start_time'], lons, lats)
sata, satel = get_observer_look(
vis.attrs['satellite_longitude'],
vis.attrs['satellite_latitude'],
vis.attrs['satellite_altitude'],
vis.attrs['start_time'],
lons, lats, 0)
satz = 90 - satel
return sata, satz, suna, sunz
def get_angles(self, vis):
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
lons, lats = vis.attrs['area'].get_lonlats_dask(chunks=vis.data.chunks)
suna = get_alt_az(vis.attrs['start_time'], lons, lats)[1]
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(vis.attrs['start_time'], lons, lats)
sat_lon, sat_lat, sat_alt = get_satpos(vis)
sata, satel = get_observer_look(
sat_lon,
sat_lat,
sat_alt / 1000.0, # km
vis.attrs['start_time'],
lons,
lats,
0)
satz = 90 - satel
return sata, satz, suna, sunz
def __call__(self, projectables, optional_datasets=None, **info):
"""Get the corrected reflectance when removing Rayleigh scattering. Uses
pyspectral.
"""
from pyspectral.rayleigh import Rayleigh
(vis, ) = projectables
try:
(sata, satz, suna, sunz) = optional_datasets
except ValueError:
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
sunalt, suna = get_alt_az(vis.info['start_time'],
*vis.info['area'].get_lonlats())
sunz = sun_zenith_angle(vis.info['start_time'],
*vis.info['area'].get_lonlats())
lons, lats = vis.info['area'].get_lonlats()
sata, satel = get_observer_look(vis.info['satellite_longitude'],
vis.info['satellite_latitude'],
vis.info['satellite_altitude'],
vis.info['start_time'], lons, lats,
0)
satz = 90 - satel
LOG.info('Removing Rayleigh scattering')
ssadiff = np.abs(suna - sata)
ssadiff = np.where(np.greater(ssadiff, 180), 360 - ssadiff, ssadiff)
corrector = Rayleigh(vis.info['platform_name'],
vis.info['sensor'],
atmosphere='us-standard',
rural_aerosol=False)
refl_cor_band = corrector.get_reflectance(sunz, satz, ssadiff,
vis.info['id'].wavelength[1],
vis)
proj = Projectable(vis - refl_cor_band, copy=False, **vis.info)
self.apply_modifier_info(vis, proj)
return proj
def get_angles(self, vis):
"""Get sun and satellite angles to use in crefl calculations."""
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
lons, lats = vis.attrs['area'].get_lonlats(chunks=vis.data.chunks)
lons = da.where(lons >= 1e30, np.nan, lons)
lats = da.where(lats >= 1e30, np.nan, lats)
suna = get_alt_az(vis.attrs['start_time'], lons, lats)[1]
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(vis.attrs['start_time'], lons, lats)
sat_lon, sat_lat, sat_alt = get_satpos(vis)
sata, satel = get_observer_look(
sat_lon,
sat_lat,
sat_alt / 1000.0, # km
vis.attrs['start_time'],
lons, lats, 0)
satz = 90 - satel
return sata, satz, suna, sunz
def __call__(self, projectables, optional_datasets=None, **info):
"""Get the corrected reflectance when removing Rayleigh scattering. Uses
pyspectral.
"""
from pyspectral.rayleigh import Rayleigh
(vis,) = projectables
try:
(sata, satz, suna, sunz) = optional_datasets
except ValueError:
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
from pyorbital.orbital import get_observer_look
sunalt, suna = get_alt_az(
vis.info['start_time'], *vis.info['area'].get_lonlats())
sunz = sun_zenith_angle(
vis.info['start_time'], *vis.info['area'].get_lonlats())
lons, lats = vis.info['area'].get_lonlats()
sata, satel = get_observer_look(vis.info['satellite_longitude'],
vis.info['satellite_latitude'],
vis.info['satellite_altitude'],
vis.info['start_time'],
lons, lats, 0)
satz = 90 - satel
LOG.info('Removing Rayleigh scattering')
ssadiff = np.abs(suna - sata)
ssadiff = np.where(np.greater(ssadiff, 180), 360 - ssadiff, ssadiff)
corrector = Rayleigh(
vis.info['platform_name'], vis.info['sensor'], atmosphere='us-standard', rural_aerosol=False)
refl_cor_band = corrector.get_reflectance(
sunz, satz, ssadiff, vis.info['id'].wavelength[1], vis)
proj = Projectable(vis - refl_cor_band,
copy=False,
**vis.info)
self.apply_modifier_info(vis, proj)
return proj
def get_solar_angles(scene, lons, lats):
"""Compute solar angles.
Compute angles for each scanline using their acquisition time to account for
the earth's rotation over the course of one scan.
Returns:
Solar azimuth angle, Solar zenith angle in degrees
"""
suna = np.full(lons.shape, np.nan)
sunz = np.full(lons.shape, np.nan)
mean_acq_time = get_mean_acq_time(scene)
for line, acq_time in enumerate(mean_acq_time.values):
if np.isnat(acq_time):
continue
_, suna_line = get_alt_az(acq_time, lons[line, :], lats[line, :])
suna_line = np.rad2deg(suna_line)
suna[line, :] = suna_line
sunz[line, :] = sun_zenith_angle(acq_time, lons[line, :],
lats[line, :])
return suna, sunz
def _get_sun_azimuth_ndarray(lons: np.ndarray, lats: np.ndarray,
start_time: datetime) -> np.ndarray:
with ignore_invalid_float_warnings():
suna = get_alt_az(start_time, lons, lats)[1]
suna = np.rad2deg(suna)
return suna
lats[:, :][::1, ::1])
print(sun_zenith.shape)
#------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------
# Apply the sun zenith correction
data1 = (data1) / (np.cos(np.deg2rad(sun_zenith)))
data2 = (data2) / (np.cos(np.deg2rad(sun_zenith)))
data3 = (data3) / (np.cos(np.deg2rad(sun_zenith)))
#------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------
# Applying the Rayleigh correction
from pyorbital.astronomy import get_alt_az
from pyorbital.orbital import get_observer_look
sunalt, suna = get_alt_az(utc_time, lons, lats)
suna = np.rad2deg(suna)
#sata, satel = get_observer_look(sat_lon, sat_lat, sat_alt, vis.attrs['start_time'], lons, lats, 0)
sata, satel = get_observer_look(longitude, 0.0, sat_h, utc_time, lons, lats, 0)
satz = 90 - satel
# Reyleigh Correction
atmosphere = 'us-standard'
aerosol_type = 'rayleigh_only'
rayleigh_key = ('GOES-16', 'abi', atmosphere, aerosol_type)
corrector = Rayleigh('GOES-16',
'abi',
atmosphere=atmosphere,
aerosol_type=aerosol_type)
sata = sata % 360.
def process_one_scan(tslot_files,
out_path,
process_buggy_satellite_zenith_angles=False):
""" Make level 1c files in PPS-format """
tic = time.time()
image_num = 0 # name of first dataset is image0
#if len(tslot_files) != 8 * len(BANDNAMES) + 2:
# raise Exception("Some data is missing")
platform_shortname = p__.parse(os.path.basename(
tslot_files[0]))['platform_shortname']
start_time = p__.parse(os.path.basename(tslot_files[0]))['start_time']
platform_name = PLATFORM_SHORTNAMES[platform_shortname]
#Load channel data for one scene and set some attributes
coefs = get_calibration_for_time(platform=platform_shortname,
time=start_time)
scn_ = Scene(reader='seviri_l1b_hrit',
filenames=tslot_files,
reader_kwargs={
'calib_mode': CALIB_MODE,
'ext_calib_coefs': coefs
})
scn_.attrs['platform_name'] = platform_name
#SEVIRI data only
if scn_.attrs['sensor'] == {'seviri'}:
sensor = 'seviri'
scn_.load(BANDNAMES)
for band in BANDNAMES:
idtag = PPS_TAGNAMES[band]
scn_[band].attrs['id_tag'] = idtag
scn_[band].attrs['description'] = 'SEVIRI ' + str(band)
scn_[band].attrs['sun_earth_distance_correction_applied'] = 'False'
scn_[band].attrs['sun_earth_distance_correction_factor'] = 1.0
scn_[band].attrs['sun_zenith_angle_correction_applied'] = 'False'
scn_[band].attrs['name'] = "image{:d}".format(image_num)
scn_[band].attrs['coordinates'] = 'lon lat'
image_num += 1
#correct area
area_corr = pyresample.geometry.AreaDefinition(
'seviri-corrected', 'Corrected SEVIRI L1.5 grid (since Dec 2017)',
'geosmsg', {
'a': 6378169.00,
'b': 6356583.80,
'h': 35785831.0,
'lon_0': 0.0,
'proj': 'geos',
'units': 'm'
}, 3712, 3712, (5567248.28340708, 5570248.686685662,
-5570248.686685662, -5567248.28340708))
if not scn_['IR_108'].attrs['georef_offset_corrected']:
scn_ = scn_.resample(area_corr)
print(scn_['IR_108'].attrs['georef_offset_corrected'])
#import pdb;pdb.set_trace()
#Set som header attributes:
scn_.attrs['platform'] = platform_name
scn_.attrs['instrument'] = sensor.upper()
scn_.attrs['source'] = "seviri2pps.py"
scn_.attrs['orbit_number'] = "99999"
#scn_.attrs['orbit'] = "99999"
nowutc = datetime.utcnow()
scn_.attrs['date_created'] = nowutc.strftime("%Y-%m-%dT%H:%M:%SZ")
#Find lat/lon data
irch = scn_['IR_108']
lons, lats = irch.attrs['area'].get_lonlats()
lons[lons > 360] = -999.0
lons[lons < -360] = -999.0
lats[lats > 360] = -999.0
lats[lats < -360] = -999.0
#Find angles data
sunalt, suna = get_alt_az(irch.attrs['start_time'],
*irch.attrs['area'].get_lonlats())
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(irch.attrs['start_time'],
*irch.attrs['area'].get_lonlats())
# if:
# Buggy data is requested buggy data is prepared!
# elif:
# 1) get_observer_look() gives wrong answer ...
# ... for satellite altitude in m. AND
# 2) get_observer_look() gives correct answer ...
# .... for satellite altitude in km. AND
# 3) Satellite altitude is m.:
# => Satellite alltitude need to be converted to km.
# else:
# => There have been updates to SatPy and this script
# need to be modified.
if process_buggy_satellite_zenith_angles:
print(" Making buggy satellite zenith angels on purpose!")
sata, satel = get_observer_look(
irch.attrs['orbital_parameters']['satellite_actual_longitude'],
irch.attrs['orbital_parameters']['satellite_actual_latitude'],
irch.attrs['orbital_parameters']['satellite_actual_altitude'],
irch.attrs['start_time'], lons, lats, 0)
elif (get_observer_look(0, 0, 36000 * 1000, datetime.utcnow(),
np.array([16]), np.array([58]), np.array(
[0]))[1] > 30
and get_observer_look(0, 0, 36000, datetime.utcnow(), np.array([16]),
np.array([58]), np.array([0]))[1] < 23
and irch.attrs['orbital_parameters']['satellite_actual_altitude'] >
38000):
sata, satel = get_observer_look(
irch.attrs['orbital_parameters']['satellite_actual_longitude'],
irch.attrs['orbital_parameters']['satellite_actual_latitude'],
0.001 *
irch.attrs['orbital_parameters']['satellite_actual_altitude'],
irch.attrs['start_time'], lons, lats, 0)
else:
raise UnexpectedSatpyVersion(
"You might have a newer version of satpy/pyorbital that"
"handles units. In that case the m => km conversion might"
"be unneeded and wrong.")
satz = 90 - satel
azidiff = make_azidiff_angle(sata, suna, -32767)
#Add lat/lon and angles datasets to the scen object
my_coords = scn_['IR_108'].coords
my_coords['time'] = irch.attrs['start_time']
scn_['lat'] = xr.DataArray(da.from_array(lats, chunks=(53, 3712)),
dims=['y', 'x'],
coords={
'y': scn_['IR_108']['y'],
'x': scn_['IR_108']['x']
})
scn_['lat'].attrs['long_name'] = 'latitude coordinate'
scn_['lat'].attrs['standard_name'] = 'latitude'
scn_['lat'].attrs['units'] = 'degrees_north'
scn_['lat'].attrs['start_time'] = irch.attrs['start_time']
scn_['lat'].attrs['end_time'] = irch.attrs['end_time']
scn_['lon'] = xr.DataArray(da.from_array(lons, chunks=(53, 3712)),
dims=['y', 'x'],
coords={
'y': scn_['IR_108']['y'],
'x': scn_['IR_108']['x']
})
scn_['lon'].attrs['long_name'] = 'longitude coordinate'
scn_['lon'].attrs['standard_name'] = 'longitude'
scn_['lon'].attrs['units'] = 'degrees_east'
scn_['lon'].attrs['start_time'] = irch.attrs['start_time']
scn_['lon'].attrs['end_time'] = irch.attrs['end_time']
#sunzenith
scn_['sunzenith'] = xr.DataArray(da.from_array(sunz[:, :],
chunks=(53, 3712)),
dims=['y', 'x'],
coords=my_coords)
scn_['sunzenith'].attrs['id_tag'] = 'sunzenith'
scn_['sunzenith'].attrs['long_name'] = 'sun zenith angle'
scn_['sunzenith'].attrs['standard_name'] = 'solar_zenith_angle'
scn_['sunzenith'].attrs['valid_range'] = [0, 18000]
scn_['sunzenith'].attrs['name'] = "image{:d}".format(image_num)
image_num += 1
#satzenith
scn_['satzenith'] = xr.DataArray(da.from_array(satz[:, :],
chunks=(53, 3712)),
dims=['y', 'x'],
coords=my_coords)
scn_['satzenith'].attrs['id_tag'] = 'satzenith'
scn_['satzenith'].attrs['long_name'] = 'satellite zenith angle'
scn_['satzenith'].attrs['standard_name'] = 'platform_zenith_angle'
scn_['satzenith'].attrs['valid_range'] = [0, 9000]
scn_['satzenith'].attrs['name'] = "image{:d}".format(image_num)
image_num += 1
#azidiff
scn_['azimuthdiff'] = xr.DataArray(da.from_array(azidiff[:, :],
chunks=(53, 3712)),
dims=['y', 'x'],
coords=my_coords)
scn_['azimuthdiff'].attrs['id_tag'] = 'azimuthdiff'
#scn_['azimuthdiff'].attrs['standard_name'] = (
# 'angle_of_rotation_from_solar_azimuth_to_platform_azimuth')
scn_['azimuthdiff'].attrs[
'long_name'] = 'absoulte azimuth difference angle'
scn_['azimuthdiff'].attrs['valid_range'] = [0, 18000]
scn_['azimuthdiff'].attrs['name'] = "image{:d}".format(image_num)
image_num += 1
for angle in ['azimuthdiff', 'satzenith', 'sunzenith']:
scn_[angle].attrs['units'] = 'degree'
for attr in irch.attrs.keys():
if attr in [
"start_time", "end_time", "navigation",
"georef_offset_corrected", "projection"
]:
scn_[angle].attrs[attr] = irch.attrs[attr]
#Get filename
start_time = scn_['IR_108'].attrs['start_time']
end_time = scn_['IR_108'].attrs['end_time']
filename = os.path.join(
out_path, "S_NWC_seviri_{:s}_{:s}_{:s}Z_{:s}Z.nc".format(
platform_name.lower().replace('-', ''), "99999",
start_time.strftime('%Y%m%dT%H%M%S%f')[:-5],
end_time.strftime('%Y%m%dT%H%M%S%f')[:-5]))
#Encoding for channels
save_info = {}
for band in BANDNAMES:
idtag = PPS_TAGNAMES[band]
name = scn_[band].attrs['name']
scn_[band].attrs.pop('area', None)
# Add time coordinate. To make cfwriter aware that we want 3D data.
my_coords = scn_[band].coords
my_coords['time'] = irch.attrs['start_time']
if 'tb' in idtag:
save_info[name] = {
'dtype': 'int16',
'scale_factor': 0.01,
'_FillValue': -32767,
'zlib': True,
'complevel': 4,
'add_offset': 273.15
}
else:
save_info[name] = {
'dtype': 'int16',
'scale_factor': 0.01,
'zlib': True,
'complevel': 4,
'_FillValue': -32767,
'add_offset': 0.0
}
#Encoding for angles and lat/lon
for name in ['image11', 'image12', 'image13']:
save_info[name] = {
'dtype': 'int16',
'scale_factor': 0.01,
'zlib': True,
'complevel': 4,
'_FillValue': -32767,
'add_offset': 0.0
}
for name in ['lon', 'lat']:
save_info[name] = {
'dtype': 'float32',
'zlib': True,
'complevel': 4,
'_FillValue': -999.0
}
header_attrs = scn_.attrs.copy()
header_attrs['start_time'] = time.strftime(
"%Y-%m-%d %H:%M:%S", irch.attrs['start_time'].timetuple())
header_attrs['end_time'] = time.strftime(
"%Y-%m-%d %H:%M:%S", irch.attrs['end_time'].timetuple())
header_attrs['sensor'] = sensor.lower()
header_attrs.pop('platform_name', None)
scn_.save_datasets(writer='cf',
filename=filename,
header_attrs=header_attrs,
engine='netcdf4',
encoding=save_info,
include_lonlats=False,
pretty=True,
flatten_attrs=True,
exclude_attrs=['raw_metadata'])
print("Saved file {:s} after {:3.1f} seconds".format(
os.path.basename(filename),
time.time() - tic)) #About 40 seconds
return filename
def _get_sun_angles(self, vis, lons, lats):
from pyorbital.astronomy import get_alt_az, sun_zenith_angle
suna = get_alt_az(vis.attrs['start_time'], lons, lats)[1]
suna = np.rad2deg(suna)
sunz = sun_zenith_angle(vis.attrs['start_time'], lons, lats)
return suna, sunz
def get_satellite_geometry(startDateUTC,
lengthDays,
lon,
lat,
alt=0.0,
mission="Sentinel-2a",
tleFile="/data/tle/norad_resource_tle.txt"):
"""Calculate approximate geometry for Sentinel overpasses.
Approximate because it assumes maximum satellite elevation
is the time at which target is imaged.
:param startDateUTC: a datetime object specifying when to start prediction.
:type startDateUTC: object
:param lengthDays: number of days over which to perform calculations.
:type lengthDays: int
:param lat: latitude of target.
:type lat: float
:param lon: longitude of target.
:type lon: float
:param alt: altitude of target (in km).
:type alt: float
:param mission: mission name as in TLE file.
:type mission: str
:param tleFile: TLE file.
:type tleFile: str
:return: a python list containing instances of the sensorGeometry class arranged in date order.
:rtype: list
"""
orb = Orbital(mission, tleFile)
passes = orb.get_next_passes(startDateUTC, 24 * lengthDays, lon, lat, alt)
geom_inst = SensorGeometry()
geom_inst.date_utc = []
geom_inst.vza = []
geom_inst.vaa = []
geom_inst.sza = []
geom_inst.saa = []
for p in passes:
look = orb.get_observer_look(p[2], lon, lat, alt)
vza = 90 - look[1]
vaa = look[0]
sza = ast.sun_zenith_angle(p[2], lon, lat)
saa = np.rad2deg(ast.get_alt_az(p[2], lon, lat)[1])
if mission == 'Sentinel-1b':
if 75 < vaa < 105 and 20. < vza < 45.: # vaa usually [0, 180], testing observation times
geom_inst.date_utc.append(p[2])
geom_inst.vza.append(vza)
geom_inst.vaa.append(vaa)
geom_inst.sza.append(sza)
geom_inst.saa.append(saa)
elif mission == 'Sentinel-1a':
if 75 < vaa < 105 and 20. < vza < 45.: # vaa usually [0, 180], testing observation times
geom_inst.date_utc.append(p[2])
geom_inst.vza.append(vza)
geom_inst.vaa.append(vaa)
geom_inst.sza.append(sza)
geom_inst.saa.append(saa)
elif mission == 'Sentinel-2a':
if sza < 90 and vza < 10.3:
geom_inst.date_utc.append(p[2])
geom_inst.vza.append(vza)
geom_inst.vaa.append(vaa)
geom_inst.sza.append(sza)
geom_inst.saa.append(saa)
return geom_inst
